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The problem of finding a $k \times k$ submatrix of maximum volume of a matrix $A$ is of interest in a variety of applications. For example, it yields a quasi-best low-rank approximation constructed from the rows and columns of $A$. We show…

Numerical Analysis · Mathematics 2019-02-07 Alice Cortinovis , Daniel Kressner , Stefano Massei

A celebrated analogy between prime factorizations of integers and cycle decompositions of permutations is explored here. Asymptotic formulas characterizing semismooth numbers (possessing at most several large factors) carry over to random…

Combinatorics · Mathematics 2022-05-03 Steven Finch

This paper presents the link between stochastic approximation and clinical trials based on randomized urn models investigated in Bai and Hu (1999,2005) and Bai, Hu and Shen (2002). We reformulate the dynamics of both the urn composition and…

Probability · Mathematics 2017-01-19 Sophie Laruelle , Gilles Pagès

We compare dynamical and algebraic properties of semigroups of rational maps. In particular, we show a version of the Day-von Neumann's conjecture and give a partial positive answer to "Sushkievich's problem" for semigroups of rational…

Dynamical Systems · Mathematics 2023-09-07 Peter Makienko , Carlos Cabrera

We show that the probability for a finitely generated subgroup of the modular group, of size $n$, to be almost malnormal or non-parabolic, tends to 0 as $n$ tends to infinity -- where the notion of the size of a subgroup is based on a…

Group Theory · Mathematics 2023-11-15 Frédérique Bassino , Cyril Nicaud , Pascal Weil

For each $n$, let $A_n=(\sigma_{ij})$ be an $n\times n$ deterministic matrix and let $X_n=(X_{ij})$ be an $n\times n$ random matrix with i.i.d. centered entries of unit variance. We study the asymptotic behavior of the empirical spectral…

Probability · Mathematics 2020-08-03 Nicholas A. Cook , Walid Hachem , Jamal Najim , David Renfrew

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov…

Probability · Mathematics 2008-06-24 Lasse Leskelä

We consider semigroups of transformations (partial mappings defined on a set $A$) closed under the set-theoretic intersection of mappings treated as subsets of $A\times A$. On such semigroups we define two relations: the relation of…

Rings and Algebras · Mathematics 2013-05-28 W. A. Dudek , V. S. Trokhimenko

Given a basic compact semi-algebraic set $\K\subset\R^n$, we introduce a methodology that generates a sequence converging to the volume of $\K$. This sequence is obtained from optimal values of a hierarchy of either semidefinite or linear…

Optimization and Control · Mathematics 2015-05-13 Didier Henrion , Jean Bernard Lasserre , Carlo Savorgnan

A central question in random matrix theory is universality. When an emergent phenomena is observed from a large collection of chosen random variables it is natural to ask if this behavior is specific to the chosen random variable or if the…

Probability · Mathematics 2021-01-13 Jake Koenig , Hoi Nguyen

Extending earlier work on supertropical adjoints and applying symmetrization, we provide a symmetric supertropical version $\operatorname {SLS}_n$ of the special linear group, which we partition into submonoids, based on "quasi-identity"…

Rings and Algebras · Mathematics 2017-06-14 Zur Izhakian , Adi Niv , Louis Rowen

We are now witnessing a rapid growth of a new part of group theory which has become known as "statistical group theory". A typical result in this area would say something like ``a random element (or a tuple of elements) of a group G has a…

Group Theory · Mathematics 2007-05-23 Alexandre V. Borovik , Alexei G. Myasnikov , Vladimir Shpilrain

A generalized numerical semigroup is a submonoid $S$ of $\mathbb{N}^d$ with finite complement in it. We characterize isomorphisms between these monoids in terms of permutation of coordinates. Considering the equivalence relation that…

Combinatorics · Mathematics 2025-05-06 Carmelo Cisto , Gioia Failla , Francesco Navarra

In this short lecture, we compute asymptotics of orthogonal polynomials, from a saddle point approximation. This is an example of a calculation which shows the link between integrability, algebraic geometry and random matrices.

Mathematical Physics · Physics 2007-05-23 Bertrand Eynard

Assume that $S$ is a semigroup generated by $\{x_1,...,x_n\}$, and let $\Uscr$ be the multiplicative free commutative semigroup generated by $\{u_1,...,u_n\}$. We say that $S$ is of \emph{$I$-typ}e if there is a bijection $v:\Uscr\r S$ such…

Quantum Algebra · Mathematics 2007-05-23 Tatiana Gateva-Ivanova , Michel Van den Bergh

In this paper, for $\alpha\in(0,\infty)\setminus\{1\}$, $p>0$ and positive semidefinite matrices $A$ and $B$, we consider the quasi-extension $\mathcal{M}_{\alpha,p}(A,B):=\mathcal{M}_\alpha(A^p,B^p)^{1/p}$ of several $\alpha$-weighted…

Functional Analysis · Mathematics 2026-01-21 Fumio Hiai

We present nonasymptotic concentration inequalities for sums of independent and identically distributed random variables that yield asymptotic strong Gaussian approximations of Koml\'os, Major, and Tusn\'ady (KMT) [1975,1976]. The constants…

Probability · Mathematics 2025-10-01 Ian Waudby-Smith , Martin Larsson , Aaditya Ramdas

Let $S$ be an additively idempotent semiring and $\mathbf{M}_n(S)$ be the semiring of all $n\times n$ matrices over $S$. We characterize the conditions of when the semiring $\mathbf{M}_n(S)$ is congruence-simple provided that the semiring…

Rings and Algebras · Mathematics 2023-05-02 Tomáš Kepka , Miroslav Korbelář

It is shown the almost sure convergence and asymptotical normality of a generalization of Kesten's stochastic approximation algorithm for multidimensional case. In this generalization, the step increases or decreases if the scalar product…

Statistics Theory · Mathematics 2011-05-27 Pedro Cruz

Positive semi-definite matrices commonly occur as normal matrices of least squares problems in statistics or as kernel matrices in machine learning and approximation theory. They are typically large and dense. Thus algorithms to solve…

Numerical Analysis · Mathematics 2020-12-01 Markus Hegland , Frank deHoog